activity
20142024
most citedA Survey on Incomplete Multi-view Clustering

248 citations · 464 across the 37 of their papers we have counts for

collaborators

37 papers

cs.CV2024

CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network

Jie Wen, Zheng Zhang, Yong Xu +3

In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a…

cs.CV2024

PSALM: Pixelwise SegmentAtion with Large Multi-Modal Model

Zheng Zhang, Yeyao Ma, Enming Zhang +1

PSALM is a powerful extension of the Large Multi-modal Model (LMM) to address the segmentation task challenges. To overcome the limitation of the LMM being limited to textual outpu…

cs.CL2024

LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models

Yifan Yang, Jiajun Zhou, Ngai Wong +1

Various parameter-efficient fine-tuning (PEFT) techniques have been proposed to enable computationally efficient fine-tuning while maintaining model performance. However, existing…

cs.RO20241 cited

Multi-Agent Generative Adversarial Interactive Self-Imitation Learning for AUV Formation Control and Obstacle Avoidance

Zheng Fang, Tianhao Chen, Dong Jiang +2

Multiple autonomous underwater vehicles (multi-AUV) can cooperatively accomplish tasks that a single AUV cannot complete. Recently, multi-agent reinforcement learning has been intr…

cs.LG2024

Non-Euclidean Spatial Graph Neural Network

Zheng Zhang, Sirui Li, Jingcheng Zhou +4

Spatial networks are networks whose graph topology is constrained by their embedded spatial space. Understanding the coupled spatial-graph properties is crucial for extracting powe…

cs.LG20244 cited

Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training

Yequan Zhao, Xian Xiao, Xinling Yu +5

Solving partial differential equations (PDEs) numerically often requires huge computing time, energy cost, and hardware resources in practical applications. This has limited their…